Evidence and therapeutic implications of biomechanically regulated immunosurveillance in cancer and other diseases.

Disease progression is usually accompanied by changes in the biochemical composition of cells and tissues and their biophysical properties. For instance, hallmarks of cancer include the stiffening of tissues caused by extracellular matrix remodelling and the softening of individual cancer cells. In this context, accumulating evidence has shown that immune cells sense and respond to mechanical signals from the environment. However, the mechanisms regulating these mechanical aspects of immune surveillance remain partially understood. The growing appreciation for the 'mechano-immunology' field has urged researchers to investigate how immune cells sense and respond to mechanical cues in various disease settings, paving the way for the development of novel engineering strategies that aim at mechanically modulating and potentiating immune cells for enhanced immunotherapies. Recent pioneer developments in this direction have laid the foundations for leveraging 'mechanical immunoengineering' strategies to treat various diseases. This Review first outlines the mechanical changes occurring during pathological progression in several diseases, including cancer, fibrosis and infection. We next highlight the mechanosensitive nature of immune cells and how mechanical forces govern the immune responses in different diseases. Finally, we discuss how targeting the biomechanical features of the disease milieu and immune cells is a promising strategy for manipulating therapeutic outcomes.

Rational Design of Chemically Controlled Antibodies and Protein Therapeutics.

Protein-based therapeutics, such as monoclonal antibodies and cytokines, are important therapies for various pathophysiological conditions such as oncology, autoimmune disorders, and viral infections. However, the wide application of such protein therapeutics is often hindered by dose-limiting toxicities and adverse effects, namely, cytokine storm syndrome, organ failure, and others. Therefore, spatiotemporal control of the activities of these proteins is crucial to further expand their application. Here, we report the design and application of small-molecule-controlled switchable protein therapeutics by taking advantage of a previously engineered OFF-switch system. We used the Rosetta modeling suite to computationally optimize the affinity between B-cell lymphoma 2 (Bcl-2) protein and a previously developed computationally designed protein partner (LD3) to obtain a fast and efficient heterodimer disruption upon the addition of a competing drug (Venetoclax). The incorporation of the engineered OFF-switch system into anti-CTLA4, anti-HER2 antibodies, or an Fc-fused IL-15 cytokine demonstrated an efficient disruption in vitro, as well as fast clearance in vivo upon the addition of the competing drug Venetoclax. These results provide a proof-of-concept for the rational design of controllable biologics by introducing a drug-induced OFF-switch into existing protein-based therapeutics.

Cancer-cell stiffening via cholesterol depletion enhances adoptive T-cell immunotherapy.

Malignant transformation and tumour progression are associated with cancer-cell softening. Yet how the biomechanics of cancer cells affects T-cell-mediated cytotoxicity and thus the outcomes of adoptive T-cell immunotherapies is unknown. Here we show that T-cell-mediated cancer-cell killing is hampered for cortically soft cancer cells, which have plasma membranes enriched in cholesterol, and that cancer-cell stiffening via cholesterol depletion augments T-cell cytotoxicity and enhances the efficacy of adoptive T-cell therapy against solid tumours in mice. We also show that the enhanced cytotoxicity against stiffened cancer cells is mediated by augmented T-cell forces arising from an increased accumulation of filamentous actin at the immunological synapse, and that cancer-cell stiffening has negligible influence on: T-cell-receptor signalling, production of cytolytic proteins such as granzyme B, secretion of interferon gamma and tumour necrosis factor alpha, and Fas-receptor-Fas-ligand interactions. Our findings reveal a mechanical immune checkpoint that could be targeted therapeutically to improve the effectiveness of cancer immunotherapies.

Liposome nano-formulation with cationic polar lipid DOTAP and cholesterol as a suitable pH-responsive carrier for molecular therapeutic drug (all-trans retinoic acid) delivery to lung cancer cells.

The molecular targeted drug ATRA demands a suitable carrier that delivers to the cancer site due to its poor bioavailability and drug resistance. ATRA, being a lipid with carboxylic acid, has been nano-formulated as a cationic lipo-ATRA with DOTAP:cholesterol:ATRA (5:4:1) and its pH-responsive release, intracellular drug accumulation, and anticancer effect on human lung cancer (A549) cell line analysed. The analysis of the physicochemical characteristics of the developed lipo-ATRA (0.8 µmol) revealed that the size of 231 ± 2.35 d.nm had a zeta potential of 6.4 ± 1.19 and an encapsulation efficiency of 93.7 ± 3.6%. The ATRA release from lipo-ATRA in vitro was significantly (p ≤ 0.05) higher at acidic pH 6 compared to pH 7.5. The intracellular uptake of ATRA into lipo-ATRA-treated A549 cells was seven-fold higher (0.007 ± 0.001 mg/ml) while only three-fold uptake was observed in free ATRA treatment (0.003 ± 0.002 mg/ml). The lipo-ATRA treatment caused a highly significant (p ≤ 0.001) decrease in percent cell viability at 48 h when compared with the free ATRA treatment. Overall, the results proved that the developed lipo-ATRA has suitable physicochemical properties with enhanced ATRA release at acidic pH, while maintaining stability at physiologic pH and temperature. This resulted in an increased ATRA uptake by lung cancer cells with enhanced treatment efficiency. Hence, it is concluded that DOTAP lipo-ATRA is a suitable carrier for ATRA delivery to solid cancer cells.

Optimization of therapeutic antibodies by predicting antigen specificity from antibody sequence via deep learning.

The optimization of therapeutic antibodies is time-intensive and resource-demanding, largely because of the low-throughput screening of full-length antibodies (approximately 1 × 103 variants) expressed in mammalian cells, which typically results in few optimized leads. Here we show that optimized antibody variants can be identified by predicting antigen specificity via deep learning from a massively diverse space of antibody sequences. To produce data for training deep neural networks, we deep-sequenced libraries of the therapeutic antibody trastuzumab (about 1 × 104 variants), expressed in a mammalian cell line through site-directed mutagenesis via CRISPR-Cas9-mediated homology-directed repair, and screened the libraries for specificity to human epidermal growth factor receptor 2 (HER2). We then used the trained neural networks to screen a computational library of approximately 1 × 108 trastuzumab variants and predict the HER2-specific subset (approximately 1 × 106 variants), which can then be filtered for viscosity, clearance, solubility and immunogenicity to generate thousands of highly optimized lead candidates. Recombinant expression and experimental testing of 30 randomly selected variants from the unfiltered library showed that all 30 retained specificity for HER2. Deep learning may facilitate antibody engineering and optimization.

Cytokine engineering for targeted cancer immunotherapy.

Cytokines are key modulators of the immune responses and represent promising therapeutics for a variety of cancers. However, successful translation of cytokine-based therapy to the clinic is limited by, among others, severe toxicities and lack of efficacy due to cytokine pleiotropy and off-target activation of cells. Engineering cytokines with enhanced therapeutic properties has emerged as a promising strategy to overcome these challenges. Advances in protein engineering and protein-polymer conjugate technologies have fostered the generation of cytokines with enhanced target cell specificity and longer half-life than the native ones. These novel cytokines exhibit reduced systemic toxicities while focusing the activities at the tumor site, thus, enhancing antitumor immunity. The growing toolbox of cytokine engineering strategies will further stimulate the development of smart cytokine-based immunotherapies with enhanced efficacy and safety profiles.

Glass Leachables as a Nucleation Factor for Free Fatty Acid Particle Formation in Biopharmaceutical Formulations.

Surfactants are essential components in protein formulations protecting them against interfacial stress. One of the current industry-wide challenges is enzymatic degradation of parenteral surfactants such as polysorbate 20 (PS20) and polysorbate 80, which leads to the accumulation of free fatty acids (FFAs) potentially forming visible particles over the drug product shelf-life. While the concentration of FFAs can be quantified, the time point of particle formation remains unpredictable. In this work, we studied the influence of glass leachables as nucleation factors for FFA particle formation. We demonstrate the feasibility of nucleation of FFA particles in the presence of inorganic salts like NaAlO2 and CaCl2 simulating relevant glass leachables. We further demonstrate FFA particle formation depending on relevant aluminum concentrations. FFA particle formation was subsequently confirmed with lauric/myristic acid in the presence of different quantities and compositions of glass leachables obtained by several sterilization cycles using different types of glass vials. We further verified the formation of particles in aged protein formulation containing degraded PS20 through the spiking of glass leachables. Particles were characterized as a complex of glass leachables, such as aluminum and FFAs. Based on our findings, we propose a likely pathway for FFA particle formation that considers specific nucleation factors.

Molecular Design, Optimization, and Genomic Integration of Chimeric B Cell Receptors in Murine B Cells.

Immune cell therapies based on the integration of synthetic antigen receptors comprise a powerful strategy for the treatment of diverse diseases, most notably T cells engineered to express chimeric antigen receptors (CAR) for targeted cancer therapy. In addition to T lymphocytes, B lymphocytes may also represent valuable immune cells that can be engineered for therapeutic purposes such as protein replacement therapy or recombinant antibody production. In this article, we report a promising concept for the molecular design, optimization, and genomic integration of a novel class of synthetic antigen receptors, chimeric B cell receptors (CBCR). We initially optimized CBCR expression and detection by modifying the extracellular surface tag, the transmembrane regions and intracellular signaling domains. For this purpose, we stably integrated a series of CBCR variants using CRISPR-Cas9 into immortalized B cell hybridomas. Subsequently, we developed a reliable and consistent pipeline to precisely introduce cassettes of several kb size into the genome of primary murine B cells also using CRISPR-Cas9 induced HDR. Finally, we were able to show the robust surface expression and antigen recognition of a synthetic CBCR in primary B cells. We anticipate CBCRs and our approach for engineering primary B cells will be a valuable tool for the advancement of future B cell- based immune cell therapies.

Ameliorating effect of lipo-ATRA treatment on the expression of TIG3 and its suppressing effect on PPARγ gene expression in lung cancer animal model.

This study aimed to find out the molecular therapeutic effect of lipo-ATRA on tumour suppressor TIG3 and cell proliferative biomarker PPARγ in B (a) P-induced lung cancer model. In RT-PCR study, ATRA- and lipo-ATRA-treated mice samples showed relatively higher TIG3 expression and decreased PPARγ expression (Band density) than cancer control. Among treatments, lipo-ATRA showed vital effect than free ATRA by enhancing TIG3 and decreasing PPARγ. The qPCR results also showed significant (p ≤ 0.05) difference in both TIG3 and PPAR (RQ values of TIG3, lipo-ATRA 23.85 ± 1.29; free ATRA 10.43 ± 1.81 and for PPARγ, lipo-ATRA 4.707 ± 1.21; free ATRA 15.78 ± 2.34). From this, we conclude that liposomal ATRA formulation is most preferable for prolonged delivery of ATRA at targeted site to favour molecular action. It implies that the therapeutic effect of lipo-ATRA in lung cancer was exhibited by ameliorating the TIG3 expression and by suppressing the expression of PPARγ.